Stats.Blue
Go Back

Single-Parameter Bootstrap Confidence Interval Calculator



  • Bootstrap methods assume that our sample is an SRS and will give trustworthy conclusions only if this condition is met.

  • These methods make no assumptions about the distribution your data comes from.

  • For inference for a single population mean, single-parameter bootstrap tests are an alternative to the one-sample $t$-confidence interval when the guidelines for its use are not met (such as when the data is strongly skewed or has outliers with low sample size).

  • For inference for a single population proportion, single-parameter bootstrap tests are an alternative to the one-sample $z$-confidence interval when the guidelines for its use are not met, that is when the number of successes and failures are not large enough.
DataFrequencies
Sample data goes here (enter numbers in columns):
Number of SuccessesSample Size
Calculate Interval for a:
Level of Confidence:
Number of Bootstrap Samples:
Input data as Frequency Table:



Population Mean

Sample Size: $n=$
Sample Mean: $\overline{x}=$
Confidence Interval for the True Mean:

Frequency
Sample Data Bootstrap Means $\mu^*$

Population Proportion

Sample Size: $n=$
Sample Proportion: $\hat{p}=$
Confidence Interval for the True Proportion:

Frequency
Failures and Successes Bootstrap Proportions $p^*$

Population Median

Sample Size: $n=$
Sample Median: $M=$
Confidence Interval for the True Median:

Frequency
Sample Data Bootstrap Medians $M^*$

Population Standard Deviation

Sample Size: $n=$
Sample Standard Deviation: $s=$
Confidence Interval for the True Standard Deviation:

Frequency
Sample Data Bootstrap Standard Deviations $\sigma^*$